When a digital image sensor measures light at individual locations or picture elements (pixels), the measurements are not exact but rather include noise. Picture noise can degrade the subjective quality of a digital picture. Typically, digital image capture devices (e.g., cameras) incorporate some form of image processing to reduce picture noise.
Conventional picture noise reduction techniques all have drawbacks. Fundamentally, the “true” (noise free) pixel value is impossible to determine exactly. Thus, any method that changes the pixel values of a digital picture to reduce noise will also distort the picture in other ways. Consequently, the noise reduction method itself can degrade the subjective quality of the digital picture.
Sharpening can improve the subjective quality of a picture. However, in some cases or some areas of a picture, sharpening, or sharpening too much, can degrade the subjective quality. For example, sharpening noise increases the perception of the noise and, therefore, can degrade the subjective quality. Typically, noise is more visible and objectionable on smooth, flat, areas. Thus, using more noise reduction and/or less sharpening in smooth areas, as opposed to non-smooth areas, is generally desirable.
It would be desirable to implement a tone based non-smooth detection.